Dynamic Resource Allocation Algorithms to Minimise Energy Consumption in Cloud Computing

Computer Engineering

Abstract: The exponential growth of cloud computing services has significantly increased energy consumption in data centres, posing challenges in terms of environmental sustainability and operational costs. In response, dynamic resource allocation algorithms have emerged as effective tools to minimise energy consumption by efficiently managing computational resources in cloud environments. This paper presents a comprehensive review of dynamic resource allocation algorithms aimed at addressing this critical issue in cloud computing. The review categorises these algorithms based on their underlying techniques, including workload prediction, resource provisioning, and load balancing strategies. Furthermore, it examines the state-of-the-art approaches within each category, highlighting their strengths, weaknesses, and potential for energy savings. The analysis emphasises the importance of considering various factors such as workload variability, resource heterogeneity, and scalability requirements when designing and implementing these algorithms in real-world cloud infrastructures. Additionally, the paper discusses the challenges and opportunities associated with the practical deployment of these algorithms, including issues related to system complexity, overheads, and trade-offs between energy efficiency and performance. By synthesising insights from existing research, this review provides valuable guidance for researchers and practitioners aiming to develop more energy-efficient cloud computing systems. Ultimately, the adoption of dynamic resource allocation algorithms has the potential to significantly reduce the environmental footprint of cloud data centres while simultaneously enhancing cost effectiveness and resource utilisation. This research contributes to advancing sustainability goals in cloud computing and fostering the adoption of energy-efficient practices across the industry

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